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author | Giorgio Arena <giorgio.arena@arm.com> | 2018-04-23 16:16:21 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:51:17 +0000 |
commit | ad0c7388f6261989a268ffb2d042f2bd80736e3f (patch) | |
tree | 84a0f1accc9a7c4b820f150e4265525c08a67ccf /tests/validation | |
parent | 1ed442a9b4024741860106cd96f5f7535a38fd04 (diff) | |
download | ComputeLibrary-ad0c7388f6261989a268ffb2d042f2bd80736e3f.tar.gz |
COMPMID-1068 Create validate method to CLDepthWiseConvolution
Change-Id: I3301b66a8a072c6ecd0d7f2dabef350017b55ac4
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/128677
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/CL/DepthwiseConvolutionLayer.cpp | 165 |
1 files changed, 165 insertions, 0 deletions
diff --git a/tests/validation/CL/DepthwiseConvolutionLayer.cpp b/tests/validation/CL/DepthwiseConvolutionLayer.cpp index 54b7925a09..093d342ce1 100644 --- a/tests/validation/CL/DepthwiseConvolutionLayer.cpp +++ b/tests/validation/CL/DepthwiseConvolutionLayer.cpp @@ -53,6 +53,171 @@ const auto depth_multipliers = framework::dataset::make("DepthMultiplier", { 1, TEST_SUITE(CL) TEST_SUITE(DepthwiseConvolutionLayer) +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate3x3, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights + TensorInfo(TensorShape(32U, 18U, 3U), 1, DataType::F32, 0), // Mismatching input feature maps + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Unsupported weights dimensions + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::QASYMM8, 0), // Unsupported activation + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Mismatching depth multiplier + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid stride + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid biases size + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid biases dimensions + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), // Invalid output size + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Window shrink + TensorInfo(TensorShape(32U, 18U, 8U), 1, DataType::F32, 0), + TensorInfo(TensorShape(50U, 32U, 8U), 1, DataType::QASYMM8, 0), + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(5U, 5U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::QASYMM8, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 24U), 1, DataType::QASYMM8, 0), + })), + framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::S32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(24U), 1, DataType::S32, 0), + })), + framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::QASYMM8, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(32U, 18U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(30U, 16U, 16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(48U, 30U, 24U), 1, DataType::QASYMM8, 0), + })), + framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(4, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + })), + framework::dataset::make("DepthMultiplier", { 1, + 1, + 1, + 1, + 3, + 1, + 1, + 1, + 1, + 1, + 2, + 3, + })), + framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + })), + framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true, true })), + input_info, weights_info, biases_info, output_info, conv_info, depth_multiplier, act_info, expected) +{ + bool is_valid = bool(CLDepthwiseConvolutionLayer3x3::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, depth_multiplier, act_info)); + ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); +} + +DATA_TEST_CASE(ValidateGeneric, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights + TensorInfo(TensorShape(27U, 13U, 3U), 1, DataType::F32, 0), // Mismatching input feature maps + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching depth multiplier + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid biases size + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid biases dimensions + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Invalid output size + TensorInfo(TensorShape(27U, 13U, 8U), 1, DataType::F32, 0), + TensorInfo(TensorShape(32U, 13U, 8U), 1, DataType::QASYMM8, 0), + }), + framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F16, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(3U, 3U, 24U), 1, DataType::QASYMM8, 0), + })), + framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(4U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(24U), 1, DataType::S32, 0), + })), + framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), + TensorInfo(TensorShape(25U, 11U, 16U), 1, DataType::F32, 0), + TensorInfo(TensorShape(32U, 11U, 24U), 1, DataType::QASYMM8, 0), + })), + framework::dataset::make("ConvInfo", { PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 0, 0), + PadStrideInfo(1, 1, 1, 0), + })), + framework::dataset::make("DepthMultiplier", { 1, + 1, + 3, + 1, + 1, + 1, + 2, + 3, + })), + framework::dataset::make("Expected", { false, false, false, false, false, false, true, true })), + input_info, weights_info, biases_info, output_info, conv_info, depth_multiplier, expected) +{ + bool is_valid = bool(CLDepthwiseConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, depth_multiplier)); + ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + template <typename T> using CLDepthwiseConvolutionLayerFixture = DepthwiseConvolutionLayerValidationFixture<CLTensor, CLAccessor, CLDepthwiseConvolutionLayer, T>; |